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School timetabling
Generate, validate, and refine timetables with constraint-based solvers and planner control.
Juho Isola, Smootables founder
What makes automatic school timetabling reliable instead of a black-box export? Planners need visibility into constraint validation, solver progress, and manual overrides when leadership changes a rule mid-cycle. Whether they use Untis, aSc Timetables, or another established tool, they still need plain-language explanations when a run ends without a usable timetable.
Start with how to create a school timetable for the end-to-end workflow with Smootables steps at each stage.
These guides cover data preparation, generation, validation, and conflict resolution in Smootables. They help you compare AI-assisted and rule-based approaches and decide when to rerun the solver versus adjust soft constraints.
These guides cover planner process and decisions, not a Smootables product comparison. To evaluate capabilities, see automatic school timetabling software.
Guides in this topic
Select a guide below for process-focused depth on each step.
Creating a school timetable
End-to-end workflow from feasibility-checked handoff through data prep, generation, validation, conflict resolution, and publication, with Smootables steps at each stage.
Read guide →Timetable generation
What generation places, the order that keeps the grid solvable, and how manual, automatic, and mixed runs stay under planner control.
Read guide →Constraint validation
Static checks for data errors, dynamic checks for constraint problems, and the critical issues to fix before optimisation.
Read guide →Planner control
Fixed points, staffing pins, scheduling method, and the feedback to review before a change is applied.
Read guide →Data preparation
The teacher, subject, room, class, and cycle data to clean before generation, and the errors that masquerade as solver failures.
Read guide →Conflict resolution
Reading kickouts, FIT swap chains, and the point where a conflict stops being a swap problem and becomes structural.
Read guide →Can ChatGPT create a timetable?
Whether ChatGPT can produce a usable school timetable: the one documented attempt, three planning-research benchmarks, and where solver-backed automation fits instead.
Read guide →
Related product pages
- Automatic school timetabling softwareConstraint-based timetable generation built into a structured planning workspace, with pre-solve validation, infeasibility reports, and full planner editing afterwards.
- AI powered school timetablingAn AI-powered planning and timetabling workspace where constraint-based generation produces feasible schedules and a planner assistant helps you explain, tune, and improve them without bypassing your rules.
- Manual timetabling alternatives (2026)When manual timetable placement still works, when it starts to cost more than it saves, and the range of tools that take work off planners, from spreadsheets to AI-powered platforms.
See how Smootables fits your school
Book a walkthrough and we will map Smootables to your planning, workload, and timetabling process.